IT & Software

Forward Deployed Engineer III, Applied AI

Google

London · Greater London · United Kingdom

Overview

As a Forward Deployed Engineer in Applied AI, you drive the end-to-end transformation of conversational AI prototypes into production-ready solutions. You lead delivery for customer journeys, optimize agent workloads, and implement secure, scalable infrastructure during go-live. You work with cross-functional teams to balance latency, accuracy, and cost while satisfying security requirements. This role blends hands-on engineering with strategic delivery to accelerate customer value with Gemini Enterprise and other AI solutions.

Responsibilities
  • Lead delivery for conversational AI pilots and productionize PoC code with real integrations
  • Own end-to-end Customer User Journeys (CUJs) and optimize conversational flows for top priorities
  • Architect and optimize agentic workloads, including reasoning loops and tool selection, to reduce latency
  • Implement critical infrastructure: rate limiting, error handling, regional failover, monitoring, and Go-Live readiness
  • Design security perimeters (VPC, IAM, CMEK) to meet CISO requirements and enable secure RAG deployments
  • Balance latency, accuracy, and cost through optimized RAG strategies and scalable architecture
  • Develop monitoring dashboards and alerts for stable, scalable traffic during Go-Live windows
  • Collaborate with model builders and cross-functional teams to deliver fast, reliable AI solutions
  • Engage with enterprise knowledge bases and multi-agent frameworks to reduce hallucinations
Key requirements
  • Bachelor’s degree or equivalent practical experience
  • 2 years of software development experience in Python or C++
  • 2 years of GenAI techniques or related concepts (LLMs, multi-modal, large vision models)
  • 1 year of AI/ML infrastructure experience (deployment, evaluation, optimization, data processing, debugging)
  • Experience developing and deploying multilingual natural language processing models
  • Versatility and leadership
  • Collaborative mindset across cross-functional teams
  • Problem-solving and proactive communication
  • Python or C++ programming
  • GenAI techniques (LLMs, multi-modal, LVMs)
  • AI/ML infrastructure (model deployment, evaluation, optimization)

Reference: WJ-747_30429368

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